An enterprise team we worked with moved React Native adoption from <10% to about 30% while feature delivery continued. The model: migrate screen by screen, keep stable native flows in production, package React Native as native artifacts. Read case study: clstk.com/3TLyWcY

Checking an invitation panel means recreating the invitation every time. With Appduct, an AI agent can call a function your team writes to trigger the panel with test data, wait until it’s ready, and inspect the UI. See how: clstk.com/4smYoCo

Put @apex__ai on a React issue from your backlog 🔎 It currently ranks #2 in ReactBench’s Fixing React category: finding and fixing problems in existing code while preserving behavior. Try it in your repo: clstk.com/3VJmM4Z

What evidence would make you comfortable shipping an agent’s changes? Join us in Amsterdam on Oct 22 for three talks with speakers from Callstack, @expo, @jetbrains, and Chromatic. Sign up here 👉 luma.com/i8wkxgyg

The printed report is out in the wild. Want a digital copy now, before you catch us in person? Download it at clstk.com/47MgFj7 React Native at Scale 2026 draws on conversations with 12 organizations and a decade of our React Native work.

Turn mobile designs into working features with a lower-cost AI model. @thymikee will explain the verification loops behind a rise from 60% to 98% of PRs merged on the first attempt in the workflow he’ll present. Oct 22 · Amsterdam · Save your spot: clstk.com/3WynEcJ

Keep control of what ships when agents write your UI. Craig Walker and @KasperPeulen explore how to steer and verify agent-generated UI with Storybook’s agent-native CLI and WebStorm’s design-to-browser workflows. Save your spot at clstk.com/4BbFhz5

Keep app iteration fast as your project grows. @cedric_dev will demo agents verifying changes in parallel on cloud simulators with Expo and EAS, returning evidence for human review. 📆 Oct 22 · Amsterdam · Save your spot: clstk.com/4zxtfye

Dubai, thanks for joining us at DevDay Exchange Community with our CEO and Codex Ambassador @grabbou and @OpenAIDevs! We’re planning community demos at the next meetup. Building with Codex or the @OpenAI API? Join our WhatsApp group for updates ➡️ chat.whatsapp.com/DWdJlI0bdD…

Agent retries add up 📈 In our React Native evals, @apex__ai scored 87.8% on task requirements; Claude Opus 5.5 scored 88.6%. Apex’s lower estimated model cost leaves more room to iterate. Try it on a task from your repo: clstk.com/4s8cyab

Give a React Native component its own window on Meta Quest. The Meta VR Layout SDK keeps it in the same React tree, with props and context intact. Watch both counters update, then build your own second panel: More on our blog: clstk.com/4dGqgeA

AI makes it tempting to add every feature in sight. Can the product handle 1,000 users an hour? What will 10,000 cost? @syke explains why scale and quality need to be part of the agent workflow. Chapters: 00:00 Faster coding, same deployment bottleneck 00:54 Meet Matt Hargett 02:07 QA at McAfee in 1997 07:19 Product economics and estimation 11:49 Mapping the SDLC in the AI era 16:25 Shipping, quality, and operating costs 22:34 Delegating to agents: goals and guardrails 25:21 Coverage-guided fuzzing explained 28:06 Overnight testing and repair loops 30:06 How agents change engineering roles 36:55 Do agents still need Jira tickets? 44:16 Using customer pain to prioritize improvements 49:41 Finding your next delivery bottleneck 54:07 Phased deployments, staging, and telemetry 57:06 Examining how teams really work 01:01:18 Improving the SDLC incrementally 01:03:06 Measuring outcomes and getting outside help 01:06:52 Closing thoughts

Use @apex__ai in your usual coding agent or wire it into your own tooling. The API is OpenAI- and Anthropic-compatible, so you can keep your workflow. Get API access: clstk.com/47icZ8o